Link prediction in complex networks based on the interactions among paths
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DOI: 10.1016/j.physa.2018.06.051
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Citations
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Cited by:
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- Shugang Li & Ziming Wang & Beiyan Zhang & Boyi Zhu & Zhifang Wen & Zhaoxu Yu, 2022. "The Research of “Products Rapidly Attracting Users” Based on the Fully Integrated Link Prediction Algorithm," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
- Kart, Ozge & Ulucay, Oguzhan & Bingol, Berkay & Isik, Zerrin, 2020. "A machine learning-based recommendation model for bipartite networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
- Chen Yang & Tingting Liu & Xiaohong Chen & Yiyang Bian & Yuewen Liu, 2020. "HNRWalker: recommending academic collaborators with dynamic transition probabilities in heterogeneous networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 429-449, April.
- Chi, Kuo & Qu, Hui & Yin, Guisheng, 2022. "Link prediction for existing links in dynamic networks based on the attraction force," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
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Keywords
Complex networks; H-index; Link prediction; Resource receiving process;All these keywords.
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